docstr: Test that the forecasting window transformer can be used in a pipeline
docstr_tok: ["Test","that","the","forecasting","window","transformer","can","be","used","in","a","pipeline"]
code: def test_transformers_pipeline(self):
      """
      Test that the forecasting window transformer can be used in a pipeline
  
      """
  
      times1 = pd.date_range("20130101", "20130110")
      series_1 = TimeSeries.from_times_and_values(
          times1, np.array(range(1, 11))
      )
  
      expected_transformed_series = TimeSeries.from_times_and_values(
          times1,
          np.array([100, 15, 30, 45, 60, 75, 90, 105, 120, 135]),
          columns=["rolling_sum_3_2_0"],
      )
  
      # adds NaNs
      window_transformations = [
          {
              "function": "sum",
              "mode": "rolling",
              "window": 3,
              "min_periods": 2,
          }
      ]
  
      def times_five(x):
          return x * 5
  
      mapper = Mapper(fn=times_five)
  
      window_transformer = WindowTransformer(
          transforms=window_transformations, treat_na=100
      )
  
      pipeline = Pipeline([mapper, window_transformer])
  
      transformed_series = pipeline.fit_transform(series_1)
  
      assert transformed_series == expected_transformed_series
  
file_path: darts/darts/tests/dataprocessing/transformers/test_window_transformations.py
imports: import itertools
  import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.pipeline import Pipeline
  from darts.dataprocessing.transformers import Mapper, WindowTransformer
label_desc: Use image node_id 3 for calling the TestWindowTransformer obj's underlying member method code with example usage: obj.test_transformers_pipeline() and returns: unknown